Forecasting daily gas load with OIHF-Elman neural network
Article
Zhou, Hong, Su, Gang and Li, Guofang. 2011. "Forecasting daily gas load with OIHF-Elman neural network." Procedia Computer Science. 5, pp. 754-758. https://doi.org/10.1016/j.procs.2011.07.100
| Article Title | Forecasting daily gas load with OIHF-Elman neural network |
|---|---|
| ERA Journal ID | 124626 |
| Article Category | Article |
| Authors | Zhou, Hong (Author), Su, Gang (Author) and Li, Guofang (Author) |
| Editors | Shakshuld, Elhadi and Younas, Muhammad |
| Journal Title | Procedia Computer Science |
| Journal Citation | 5, pp. 754-758 |
| Number of Pages | 5 |
| Year | 2011 |
| Place of Publication | Amsterdam, Netherlands |
| ISSN | 1877-0509 |
| Digital Object Identifier (DOI) | https://doi.org/10.1016/j.procs.2011.07.100 |
| Web Address (URL) | http://www.sciencedirect.com/science/article/pii/S187705091100425X |
| Abstract | To improve the forecasting accuracy, a model for forecasting daily gas load with OIHF-Elman network involving factors such as weather, temperature and data type is proposed. Compared with the conventional Elman network, OIHF-Elman network considers not only the hidden level feedback but also the output level feedbacks. Therefore more information from limited sampling spots is collected and utilized. The simulation results show that OIHF-Elman network performs better than Elman network in terms of accuracy given limited sampling points. The new model also improves the generalization of information and can be used to forecast the daily gas load successfully. |
| Keywords | OIHF-Elman neural network; daily gas load; forecasting |
| ANZSRC Field of Research 2020 | 490108. Operations research |
| 469999. Other information and computing sciences not elsewhere classified | |
| 380205. Time-series analysis | |
| Public Notes | © 2011 Published by Elsevier Ltd. Permanent restricted access to published version due to publisher copyright policy. |
| Byline Affiliations | Department of Electrical, Electronic and Computer Engineering |
| Tianjin Chengjian University, China | |
| Event | 2nd International Conference on Ambient Systems, Networks and Technologies (ANT 2011) |
| Institution of Origin | University of Southern Queensland |
| Event Details | 2nd International Conference on Ambient Systems, Networks and Technologies (ANT 2011) Event Date 19 to end of 21 Sep 2011 Event Location Niagara Falls, ON. Canada |
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